Publications

Modal parameter identification has received much attention recently for their usefulness in earthquake engineering, damage detection and structural health monitoring. The identification method based on Matrix Pencil technique is adopted in this paper to identify structural modal parameters, such as natural frequencies, damping ratios and modal shapes using impulse vibration responses. This method can also be applied to dynamic responses induced by stationary and white-noise inputs since the auto- and cross-correlation function of the two outputs has the same form as the impulse response dynamic functions. Matrix Pencil method is very robust to noise contained in the measurement data. It has a lower variance of estimates of the parameters of interest than the Polynomial Method, and is also computationally more efficient. The numerical simulation results show that this technique can identify modal parameters accurately even if the noise level is high.

Sliding base-isolation systems used in bridges reduce pier drifts, but at the expense of increased bearing displacements under near-source pulse-type earthquakes. It is common practice to incorporate supplemental passive non-linear dampers into the isolation system to counter increased bearing displacements. Non-linear passive dampers can certainly reduce bearing displacements, but only with increased isolation level forces and pier drifts. The semi-active controllable non-linear dampers, which can vary damping in real time, can reduce bearing displacements without further increase in forces and pier drifts; and hence deserve investigation. In this study performance of such a 'smart' sliding isolation system, used in a 1:20 scaled bridge model, employing semi-active controllable magneto-rheological (MR) dampers is investigated, analytically and experimentally, under several near-fault earthquakes. A non-linear analytical model, which incorporates the non-linearities of sliding bearings and the MR damper, is developed. A Lyapunov control algorithm for control of the MR damper is developed and implemented in shake table tests. Analytical and shake table test results are compared. It is shown that the smart MR damper reduces bearing displacements further than the passive low- and high-damping cases, while maintaining isolation level forces less than the passive high-damping case. Copyright © 2005 John Wiley & Sons, Ltd.

In recent years, magneto-rheological (MR) dampers have been used to control the response of structures. This paper presents the design and application of an H ∞ fault detection and isolation (FDI) filter and fault tolerant controller (FTC) for truss vibration control systems using MR dampers. A linear matrix inequality formulation is used to design a full order robust H∞ filter to estimate faulty input signals. A fault tolerant H ∞ controller is designed for the combined system of plant and filter, minimizing the control objective selected in the presence of disturbances and faults. A truss structure with an MR damper is used to validate the FDI and FTC controller design through numerical simulations. The residuals obtained from the filter through simulation clearly identify the fault signals. The simulation results of the proposed FTC controller confirm its effectiveness for vibration suppression of the faulty truss system.

The application of particle-based stochastic filters to acoustic emission source localization in plate structures is presented. The approach employs time-of-flight measurements of guided waves using triangulation to estimate the acoustic emission source coordinates in a probabilistic framework using Bayesian inference, incorporating uncertainties related to material properties, measurement noise, and geometry of the system of interest. The estimate of the source location is given by a probability density function conditional on the guided wave measurements, found using particle-based stochastic simulation algorithms; in this setting, a set of particles is used to explore the space of possible source locations and efficiently estimate the posterior. The use of 2 filters is explored: the ensemble Kalman filter and the particle filter. The former filter assumes that the posterior distribution can be approximated by a Gaussian distribution, although the latter provides a nonparametric estimate of the posterior in the form of a weighted set of samples, overcoming the challenges related to the evaluation of high-dimensional integrals in an efficient way. Results of an experimental validation study conducted in a laboratory environment demonstrate the accuracy and efficiency of the particle filter-based approach. In particular, it is shown that the proposed particle filter-based approach has the capability to locate the emission source under minimal instrumentation, providing confidence intervals as a quantitative measure of the uncertainty in the estimates.

This paper presents the problem definition of the benchmark structural control problem for the seismically excited highway bridge. The benchmark problem is based on the newly constructed 91/5 highway over-crossing in southern California. The goal of this benchmark effort is to develop a standardized model of a highway bridge using which competing control strategies, including devices, algorithms and sensors, can be evaluated comparatively. To achieve this goal, a 3D finite-element model is developed in MATLAB to represent the complex behavior of the full-scale highway over-crossing. The nonlinear behavior of center columns and isolation bearings is considered in formulating the bilinear force–deformation relationship. The effect of soil–structure interaction is considered by modeling the interaction by equivalent spring and dashpot. The ground motions are considered to be applied simultaneously in two directions. A MATLAB-based nonlinear structural analysis tool has been developed and made available for nonlinear dynamic analysis. Control devices are assumed to be installed between the deck and the end abutments of the bridge. Evaluation criteria and control constraints are specified for the design of controllers. Passive, semi-active and active devices and algorithms can be used to study the benchmark model. The participants in this benchmark study are required to define their control devices, sensors and control algorithms, evaluate and report the results of their proposed control strategies. Copyright © 2009 John Wiley & Sons, Ltd.

It is known that the performance of traditional passive tuned mass dampers (TMDs) is highly sensitive to vibration frequency. The fundamental frequency of existing tall buildings may shift to lower value due to damage or other reasons. In this regard, this paper deals with the resultant detuning problems of a traditional passive TMD for vibration control by retrofitting it with a passive adaptive negative stiffness device (NSD). The applied NSD not only provides negative stiffness for adjusting the TMD's de-tuned stiffness at its working stage, but also offers a fail-safe limiting stop for the TMD at large deformation/stroke. In this study, compared to the original TMD, a novel TMD-NSD assembly is proposed that is shown to be more effective for serviced structures. For example, the original TMD can only provide about 2.83% additional damping ratio to frequency-changed structures, while the newly proposed TMD-NSD further improves the damping ratio to 5.34%. Moreover, in the study it is found that the TMD-NSD also outperforms the TMD in resisting dynamic lateral loading such as along winds, cross winds, and earthquakes.

Output-only algorithms are needed for modal identification when only structural responses are available. The recent years have witnessed the fast development of blind source separation (BSS) as a promising signal processing technique, pursuing to recover the sources using only the measured mixtures. As the most popular tool solving the BSS problem, independent component analysis (ICA) is able to directly extract the time-domain modal responses, which are viewed as virtual sources, from the observed system responses; however, it has been shown that ICA loses accuracy in the presence of higher-level damping. In this study, the modal identification issue, which is incorporated into the BSS formulation, is transformed into a time-frequency framework. The sparse time-frequency representations of the monotone modal responses are proposed as the targeted independent sources hidden in those of the system responses which have been short-time Fourier-transformed (STFT); they can then be efficiently extracted by ICA, whereby the time-domain modal responses are recovered such that the modal parameters are readily obtained. The simulation results of a multidegree-of-freedom system illustrate that the proposed output-only STFT-ICA method is capable of accurately identifying modal information of lightly and highly damped structures, even in the presence of heavy noise and nonstationary excitation. The laboratory experiment on a highly damped three-story frame and the analysis of the real measured seismic responses of the University of Southern California hospital building demonstrate the capability of the method to perform blind modal identification in practical applications.

Effectiveness of a new semiactive independently variable stiffness (SAIVS) device in reducing seismic response of sliding base isolated buildings is evaluated analytically and experimentally. Through analytical and experimental study of force—displacement behaviour of the SAIVS device, it is shown that the device can vary stiffness continuously and smoothly between minimum and maximum stiffness. Passive sliding base isolation systems reduce interstorey drifts and superstructure accelerations, but with increased base displacements, which is undesirable, under large velocity near fault pulse type earthquakes. It is a common practice to incorporate non-linear passive dampers into the isolation system to reduce bearing displacements. Incorporation of passive dampers, however, may result in increased superstructure accelerations and drifts; while, properly designed passive dampers can be beneficial. A viable alternative is to use semiactive variable stiffness systems, which can vary the period of the sliding base isolated buildings in real time, to simultaneously reduce bearing displacements and superstructure responses further than the passive systems, which deserves investigation. This study investigates the performance of a 1:5 scaled smart sliding base isolated building model equipped with the SAIVS device analytically and experimentally, under near fault earthquakes, by developing a new moving average non-linear tangential stiffness control algorithm for control of the SAIVS device. The SAIVS device reduces bearing displacements further than the passive cases, while maintaining isolation level forces and superstructure responses at the same level as the passive minimum stiffness case, indicating the significant potential of the SAIVS system. Copyright © 2005 John Wiley & Sons, Ltd.

Immediate assessment of structural integrity of important civil infrastructures, like bridges, hospitals, or dams, is of utmost importance after natural disasters. Currently, inspection is performed manually by engineers who look for local damages and their extent on significant locations of the structure to understand its implication on its global stability. However, the whole process is time-consuming and prone to human errors. Due to their size and extent, some regions of civil structures are hard to gain access for manual inspection. In such situations, a vision-based system of Unmanned Aerial Vehicles (UAVs) programmed with Artificial Intelligence algorithms may be an effective alternative to carry out a health assessment of civil infrastructures in a timely manner. This paper proposes a framework of achieving the above-mentioned goal using computer vision and deep learning algorithms for detection of cracks on the concrete surface from its image by carrying out image segmentation of pixels, i.e., classification of pixels in an image of the concrete surface and whether it belongs to cracks or not. The image segmentation or dense pixel level classification is carried out using a deep neural network architecture named U-Net. Further, morphological operations on the segmented images result in dense measurements of crack geometry, like length, width, area, and crack orientation for individual cracks present in the image. The efficacy and robustness of the proposed method as a viable real-life application was validated by carrying out a laboratory experiment of a four-point bending test on an 8-foot-long concrete beam of which the video is recorded using a camera mounted on a UAV-based, as well as a still ground-based, video camera. Detection, quantification, and localization of damage on a civil infrastructure using the proposed framework can directly be used in the prognosis of the structure's ability to withstand service loads.

Fuzzy techniques are employed for the nonlinear control of sliding-isolated structures. Base isolation of structures that are subjected to seismic excitation has been shown to be effective in reducing the forces transmitted to the superstructure. Active control, using linear control laws, applied to supplement the base isolation has proved to be effective in reducing the transmitted forces further. However, the response of a base-isolated structure is nonlinear and nondeterministic. Hence nonlinear control laws that accommodate uncertainty would yield better reduction of these forces. Fuzzy set theory and fuzzy logic provide a simple framework for specifying these complex control laws. The results obtained with the fuzzy algorithm are compared to the analytical and experimental results obtained using an instantaneous optimal control algorithm. The results demonstrate the potential of the fuzzy algorithm when applied to the hybrid control of structures.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>